- Rna Seq AnalysisBulk RNA-seq analysis pipeline covering alignment (STAR), quantification (Salmon, featureCounts), and differential expression (DESeq2). Triggers on RNA-seq, STAR, Salmon, DESeq2, differential expression, gene expression, tximport, featureCounts, transcriptomics, "bulk RNA-seq", "STAR alignment", "Salmon quantification", "gene counts", "DESeq2 results", "shrinkage estimator", "volcano plot RNA-seq".awslabs/hcls-agent-skills2
- Rwd Cohort AnalysisReal-world data cohort analysis pipeline for claims and EHR data — cohort identification with ICD-10, NDC, and CPT codes, medication adherence metrics (PDC/MPR), propensity score estimation and balance diagnostics, Kaplan-Meier survival curves, and Cox proportional hazards models. Use when the user mentions claims data, cohort identification, ICD-10 codes, NDC codes, CPT codes, medication adherence, PDC, MPR, propensity score, SMD balance, Kaplan-Meier, Cox model, Schoenfeld residuals, survival awslabs/hcls-agent-skills2
- Scrna Seq PipelineScanpy-based single-cell RNA-seq analysis pipeline covering loading (10X, h5ad), QC, normalization, HVG selection, PCA/UMAP, Leiden clustering, differential expression, and batch correction (Harmony, scVI). Use when the user mentions single-cell, scRNA-seq, Scanpy, AnnData, UMAP, clustering, 10X, h5ad, leiden, highly variable genes, Harmony, scVI, cluster cells, find marker genes, filter low-quality cells, gene expression matrix, doublet removal, normalize counts, dimensionality reduction, cell awslabs/hcls-agent-skills2
- Structure Based Drug DesignReasoning skill for structure-based drug design strategy. Use when the user asks to assess target druggability, choose a docking strategy, select a scoring function, define a binding site, interpret docking results, plan molecular dynamics or free energy perturbation (FEP), design a virtual screening cascade, or decide between fragment-based and HTS screening. Triggers include "drug design", "druggability", "docking strategy", "scoring function", "binding pocket", "molecular dynamics", "FEP", "Sawslabs/hcls-agent-skills2
- Trajectory AnalysisSingle-cell trajectory inference pipeline covering diffusion pseudotime (DPT), PAGA, RNA velocity with scVelo, and fate mapping with CellRank. Use when the user mentions pseudotime, trajectory, lineage, differentiation, RNA velocity, scVelo, CellRank, PAGA, diffusion map, fate probabilities, terminal states, spliced/unspliced, velocyto, order cells by development, cell differentiation path, cell fate, branching analysis, monocle, developmental trajectory, stem cell differentiation, progenitor toawslabs/hcls-agent-skills2
- Translational ResearchReason about translational research problems in HCLS — especially neurology and hypothesis validation. Use when the user asks to design a validation study, evaluate a target, qualify a biomarker, choose endpoints, critique a preclinical-to-clinical plan, pick a trial design (basket/umbrella/platform), plan multimodal data integration, or assess whether a hypothesis is ready to advance. Triggers include phrases like "validate target", "biomarker context of use", "bench to bedside", "T0/T1/T2/T3/Tawslabs/hcls-agent-skills2
- Variant CallingGermline and somatic short-variant calling pipeline for Illumina short-read data. Use when the user mentions BWA, BWA-MEM2, GATK, HaplotypeCaller, Mutect2, VCF, GVCF, VQSR, variant calling, germline, somatic, SNV, or indel calling from FASTQ/BAM.awslabs/hcls-agent-skills2